{
    "policy_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
        "__module__": "stable_baselines3.common.policies",
        "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ",
        "__init__": "<function ActorCriticPolicy.__init__ at 0x7fe4b5b38700>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe4b5b38790>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe4b5b38820>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe4b5b388b0>",
        "_build": "<function ActorCriticPolicy._build at 0x7fe4b5b38940>",
        "forward": "<function ActorCriticPolicy.forward at 0x7fe4b5b389d0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe4b5b38a60>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7fe4b5b38af0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe4b5b38b80>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe4b5b38c10>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe4b5b38ca0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7fe4b5b2fba0>"
    },
    "verbose": 1,
    "policy_kwargs": {
        ":type:": "<class 'dict'>",
        ":serialized:": "gAWVaAAAAAAAAAB9lCiMDWFjdGl2YXRpb25fZm6UjBt0b3JjaC5ubi5tb2R1bGVzLmFjdGl2YXRpb26UjARSZUxVlJOUjAhuZXRfYXJjaJRdlH2UKIwCcGmUXZQoS0BLQGWMAnZmlF2UKEtAS0BldWF1Lg==",
        "activation_fn": "<class 'torch.nn.modules.activation.ReLU'>",
        "net_arch": [
            {
                "pi": [
                    64,
                    64
                ],
                "vf": [
                    64,
                    64
                ]
            }
        ]
    },
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "gAWVdwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLBIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAD//3////9//9sPScD//3//lGgKSwSFlIwBQ5R0lFKUjARoaWdolGgSKJYQAAAAAAAAAP//f3///39/2w9JQP//f3+UaApLBIWUaBV0lFKUjA1ib3VuZGVkX2JlbG93lGgSKJYEAAAAAAAAAAEBAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLBIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYEAAAAAAAAAAEBAQGUaCFLBIWUaBV0lFKUjApfbnBfcmFuZG9tlE51Yi4=",
        "dtype": "float32",
        "_shape": [
            4
        ],
        "low": "[-3.4028235e+38 -3.4028235e+38 -3.1415927e+00 -3.4028235e+38]",
        "high": "[3.4028235e+38 3.4028235e+38 3.1415927e+00 3.4028235e+38]",
        "bounded_below": "[ True  True  True  True]",
        "bounded_above": "[ True  True  True  True]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
        ":serialized:": "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",
        "n": 2,
        "_shape": [],
        "dtype": "int64",
        "_np_random": "RandomState(MT19937)"
    },
    "n_envs": 1,
    "num_timesteps": 102400,
    "_total_timesteps": 100000,
    "_num_timesteps_at_start": 0,
    "seed": 1,
    "action_noise": null,
    "start_time": 1670516894814637504,
    "learning_rate": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "tensorboard_log": "runs/seals/CartPole-v0__ppo__7__1670516892/seals-CartPole-v0",
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "gAWVhQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMUy9ob21lL21heGltaWxpYW4vdmVudi9saWIvcHl0aG9uMy44L3NpdGUtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flGgMdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoHn2UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP1RST9rNKDOFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
    },
    "_last_obs": null,
    "_last_episode_starts": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="
    },
    "_last_original_obs": null,
    "_episode_num": 0,
    "use_sde": false,
    "sde_sample_freq": -1,
    "_current_progress_remaining": -0.02400000000000002,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 250,
    "n_steps": 512,
    "gamma": 0.9999,
    "gae_lambda": 0.9,
    "ent_coef": 0.008508727919228772,
    "vf_coef": 0.489343896591493,
    "max_grad_norm": 0.8,
    "batch_size": 256,
    "n_epochs": 10,
    "clip_range": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "clip_range_vf": null,
    "normalize_advantage": true,
    "target_kl": null
}